Reclaiming free space in a storage system

ABSTRACT

One embodiment provides a system including a computer processor, a computer-readable hardware storage device, and program code embodied with the computer-readable hardware storage device for execution by the computer processor to implement a method that includes receiving a selection of a first blob for reclamation from a first data center. The first blob includes multiple erasure code groups. A first message is sent to a second data center indicating the first blob is to be reclaimed. A global reclamation complete message is received from the second data center. The global reclamation complete message indicates a second blob in the second data center has been reclaimed. The first data center and the second data center each maintain local blob occupancy information.

BACKGROUND

Protecting against data center loss in a data storage system is mostcommonly achieved using data replication. Data is written to a firstdata center, then copied to one or more data centers for protection.With two data centers, the system is protected against the loss of anyone data center. Typical configurations use three data centers, as theyrely on the replication to protect against certain failures local to adata center. With three data centers, data is protected against theconcurrent loss of one data center and one further error in one of theremaining data centers. Such a system is expensive, as it multiplies thestorage and network capacity required. Another prior method forprotection is to use an erasure code spread across the data centers.Some examples include symmetric code, such as 6+6P (6 data and 6 parity)and 7+5P (7 data and 5 parity). Data in a first data center is encodedlocally into the erasure code, and the spread across the data centers.Both 6+6P and 7+5P have 12 storage elements in a code stripe. These canbe spread across 3 data centers by placing 4 elements on each datacenter. Both of these codes are more efficient than replication, buthave a significant performance impact. Data is encoded into the stripein a first data center, a subset of the elements are stored on the firstdata center, and the remaining subsets are stored on the other datacenters. This means that data is not protected against any type of loss(local or data center) until the entire code stripe is stored. Thissynchronous process uses WAN bandwidth for every write and suffers fromround-trip latency. Further, such erasure codes provide very limitedprotection in cloud environments. They suffer from longreconstruct/rebuild times as such recovery requires data be transferredover the WAN. Cloud systems operate at very large scale, and there arelarge numbers of storage components in each data center. Thus, theprobability of a data center having some component failed, off line orotherwise unavailable is very high. It is therefore critical to havestrong local protection in addition to data center loss protection.

SUMMARY

Embodiments generally relate to efficiently managing data on resilientdistributed data storage systems. One embodiment provides a systemincluding a computer processor, a computer-readable hardware storagedevice, and program code embodied with the computer-readable hardwarestorage device for execution by the computer processor to implement amethod that includes receiving a selection of a first blob forreclamation from a first data center. The first blob includes multipleerasure code groups. A first message is sent to a second data centerindicating the first blob is to be reclaimed. A global reclamationcomplete message is received from the second data center. The globalreclamation complete message indicates a second blob in the second datacenter has been reclaimed. The first data center and the second datacenter each maintain local blob occupancy information.

These and other features, aspects and advantages of the embodiments willbecome understood with reference to the following description, appendedclaims and accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing environment, according to anembodiment;

FIG. 2 depicts a set of abstraction model layers, according to anembodiment;

FIG. 3 is a network architecture for verifying historical artifacts indisparate source control systems, according to an embodiment;

FIG. 4 shows a representative hardware environment that may beassociated with the servers and/or clients of FIG. 1, according to anembodiment;

FIG. 5 shows a representative distributed data storage system, accordingto one embodiment;

FIG. 6 shows an exemplar set of erasure code groups distributed acrossthree data centers, according to one embodiment;

FIG. 7 shows the results of a Monte-Carlo simulation of blob occupancy,according to an embodiment;

FIG. 8 shows the efficiency resulting from different approaches tochoosing a blob for garbage collection, according to an embodiment; and

FIG. 9 illustrates a block diagram for a method for reclaiming freespace in a storage system, according to one embodiment.

DETAILED DESCRIPTION

The descriptions of the various embodiments have been presented forpurposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. The terminologyused herein was chosen to best explain the principles of theembodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

It is understood in advance that although this disclosure includes adetailed description of cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments are capable of being implemented in conjunction with anyother type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines (VMs), and services)that can be rapidly provisioned and released with minimal managementeffort or interaction with a provider of the service. This cloud modelmay include at least five characteristics, at least three servicemodels, and at least four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded and automatically, without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneous,thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or data center).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned and, in some cases, automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active consumer accounts). Resource usage canbe monitored, controlled, and reported, thereby providing transparencyfor both the provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isthe ability to use the provider's applications running on a cloudinfrastructure. The applications are accessible from various clientdevices through a thin client interface, such as a web browser (e.g.,web-based email). The consumer does not manage or control the underlyingcloud infrastructure including network, servers, operating systems,storage, or even individual application capabilities, with the possibleexception of limited consumer-specific application configurationsettings.

Platform as a Service (PaaS): the capability provided to the consumer isthe ability to deploy onto the cloud infrastructure consumer-created oracquired applications created using programming languages and toolssupported by the provider. The consumer does not manage or control theunderlying cloud infrastructure including networks, servers, operatingsystems, or storage, but has control over the deployed applications andpossibly application-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is the ability to provision processing, storage, networks, andother fundamental computing resources where the consumer is able todeploy and run arbitrary software, which can include operating systemsand applications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting for loadbalancing between clouds).

A cloud computing environment is a service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, an illustrative cloud computing environment 50is depicted. As shown, cloud computing environment 50 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows the cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby the cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments are notlimited thereto. As depicted, the following layers and correspondingfunctions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, a management layer 80 may provide the functionsdescribed below. Resource provisioning 81 provides dynamic procurementof computing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95 and verifying historical artifacts indisparate source control systems 96. As mentioned above, all of theforegoing examples described with respect to FIG. 2 are illustrativeonly, and the embodiments are not limited to these examples.

It is understood all functions of one or more embodiments as describedherein may be typically performed in the computing environment 50 (FIG.1), the network 300 (FIG. 3), or performed by the system 400 (FIG. 4),which can be tangibly embodied as hardware processors and with modulesof program code. However, this need not be the case. Rather, thefunctionality recited herein could be carried out/implemented and/orenabled by any of the layers 60, 70, 80 and 90 shown in FIG. 2.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments may be implemented with any type of clustered computingenvironment now known or later developed.

FIG. 3 illustrates a network architecture 300, in accordance with oneembodiment. As shown in FIG. 3, a plurality of remote networks 302 areprovided, including a first remote network 304 and a second remotenetwork 306. A gateway 301 may be coupled between the remote networks302 and a proximate network 308. In the context of the present networkarchitecture 300, the networks 304, 306 may each take any formincluding, but not limited to, a LAN, a WAN, such as the Internet,public switched telephone network (PSTN), internal telephone network,etc. In one embodiment, the network architecture 300 employs a POSIX®based file system.

In use, the gateway 301 serves as an entrance point from the remotenetworks 302 to the proximate network 308. As such, the gateway 301 mayfunction as a router, which is capable of directing a given packet ofdata that arrives at the gateway 301, and a switch, which furnishes theactual path in and out of the gateway 301 for a given packet.

Further included is at least one data server 314 coupled to theproximate network 308, which is accessible from the remote networks 302via the gateway 301. It should be noted that the data server(s) 314 mayinclude any type of computing device/groupware. Coupled to each dataserver 314 is a plurality of user devices 316. Such user devices 316 mayinclude a desktop computer, laptop computer, handheld computer, printer,and/or any other type of logic-containing device. It should be notedthat a user device 311 may also be directly coupled to any of thenetworks in some embodiments.

A peripheral 320 or series of peripherals 320, e.g., facsimile machines,printers, scanners, hard disk drives, networked and/or local storageunits or systems, etc., may be coupled to one or more of the networks304, 306, 308. It should be noted that databases and/or additionalcomponents may be utilized with, or integrated into, any type of networkelement coupled to the networks 304, 306, 308. In the context of thepresent description, a network element may refer to any component of anetwork.

According to some approaches, methods and systems described herein maybe implemented with and/or on virtual systems and/or systems, whichemulate one or more other systems, such as a UNIX system that emulatesan IBM z/OS environment, a UNIX system that virtually hosts a MICROSOFTWINDOWS environment, a MICROSOFT WINDOWS system that emulates an IBMz/OS environment, etc. This virtualization and/or emulation may beimplemented through the use of VMWARE software in some embodiments.

FIG. 4 shows a representative hardware system 400 environment associatedwith a user device 316 and/or server 314 of FIG. 3, in accordance withone embodiment. In one example, a hardware configuration includes aworkstation having a central processing unit 410, such as amicroprocessor, and a number of other units interconnected via a systembus 412. The workstation shown in FIG. 4 may include a Random AccessMemory (RAM) 414, Read Only Memory (ROM) 416, an I/O adapter 418 forconnecting peripheral devices, such as disk storage units 420 to the bus412, a user interface adapter 422 for connecting a keyboard 424, a mouse426, a speaker 428, a microphone 432, and/or other user interfacedevices, such as a touch screen, a digital camera (not shown), etc., tothe bus 412, communication adapter 434 for connecting the workstation toa communication network 435 (e.g., a data processing network) and adisplay adapter 436 for connecting the bus 412 to a display device 438.

In one example, the workstation may have resident thereon an operatingsystem, such as the MICROSOFT WINDOWS Operating System (OS), a MAC OS, aUNIX OS, etc. In one embodiment, the system 400 employs a POSIX® basedfile system. It will be appreciated that other examples may also beimplemented on platforms and operating systems other than thosementioned. Such other examples may include operating systems writtenusing JAVA, XML, C, and/or C++ language, or other programming languages,along with an object oriented programming methodology. Object orientedprogramming (OOP), which has become increasingly used to develop complexapplications, may also be used.

FIG. 5 shows a representative distributed data storage system 500,according to one embodiment. The system 500 illustrates a set offederated data centers 502, 508 and 514, protected by local and globalerasure codes. In one embodiment, the global erasure code has data setson two of the data centers, and parity sets on the third data centerforming the global erasure code. While FIG. 5 details three data centers502, 508 and 514, two or more data centers is the preferred embodiment.Any number of data centers can hold the parity sets so long as there isat least one data center which has data sets. Each data center alsoprotects the local data sets with additional parity information, formingthe local erasure codes. Each data center has its own encoder/decoder504, 510 and 516, for managing the local and global codes and handlingassociated state information.

The data storage centers 502, 508 and 514 are connected over a network,such as a WAN. Each data storage center includes a plurality of dataunits 506, 512 and 518, shown as boxes labeled “Dxxx” where “x”identifies a numerical value of a particular unit (e.g., D233). The dataunits 506, 512 and 518 are further grouped into sets labeled “Box n.”These indicate some common failure domain in the data center, such as aJBOD (just a bunch of discs), or a rack, etc. As shown in FIG. 5, alayer of protection local to each data storage center is present. Inthis embodiment, these are first-responder-type erasure codes. The row,columns and global parities provide protection for local data failures.The data units 506, 512 and 518 are protected against data storagecenter failure by a cross-data-center code, such as parity.

A unit of garbage collection is called a blob. In general, a blob is aplurality of erasure code groups in order to minimize theread/modify/write activity within an erasure code group. Further, blobstructures works well with log structured data layouts, such as might beemployed by an object storage. In FIG. 5, there are 8 data sets in alocal code group (Dx00, Dx01, Dx02, Dx10, Dx11, Dx12, Dx20 and Dx21)forming the garbage collection blob. In general, there can be more thanone local code group in a blob.

FIG. 6 shows an exemplar set of erasure code groups 600 distributedacross three data centers 502, 508, 514 (see FIG. 5), according to oneembodiment. The set of erasure code groups spread across 3 data centersusing global parity rotation. Each column (DC0, DC1, DC2) shows datasets for a single data center, and each row shows the data setsbelonging to each global group. For example, data sets 0-01 and 1-01 aredata sets in global group G01, whereas data set 2-01 holds an associatedparity. It is important that garbage collection for a given data centerdoes not disrupt the global parity group, which could lead to data lossexposure. Thus, the system requires garbage collection operationsmaintain the integrity of parity groups. However, it is also importantto minimize the impact of maintaining this integrity.

One embodiment uses a cooperative method to maintain the integrity ofthe global code groups while minimizing the associated writeamplification. Each data center maintains a garbage collection blob listincluding the local blob occupancy. Global parity groups do not requiresuch information as the global parity groups do not hold any data. Forlog structured systems, such as object stores, data in a blob may bedeleted, but not updated in place. In such situations the blob occupancymap need not be fully up to date, although it is beneficial. Bloboccupancy maps are asynchronously shared by the data centers, such as byperiodic or on-demand updates. Non-local blob maps may be somewhat outof date without any adverse impact on integrity of the system.

Each data center can determine the need for garbage collectionindependently, but needs to inform other data centers which local blobsare being collected. When a blob is garbage collected, the occupied datasets are read from the storage media and placed into the local datacenter's write stream for encoding into a different local erasure codegroup than its original one. The local group is then marked asunoccupied (e.g., no active data, but held for global parity). The otherdata centers in the system are informed that the local garbagecollection is complete. The other data centers collect their local blobsassociated with the global group, and inform the parity data center whencomplete. The parity data center, in turn, collects the completionmessages from the other data centers. Once the parity data centerreceives all of the completion notices, it can mark the local paritygroup associated with the global group as freed, and inform the otherdata centers that they may now mark the associated local groups as free.At this point, the entire global group of blobs has been garbagecollected.

Alternative embodiments exist for selecting blobs for garbagecollection. Having access to the blob occupancy maps for all the datacenters allows for global optimization of the selection process. Suchaccess may be provided by having asynchronous exchange of blob occupancymaps between the data centers. It is not necessary for the global blobinformation to be up to date in all the data centers. Out of date globalblob information may lead to suboptimal selection of a blob(s) forgarbage collection, but the impact to the system should be minimal. Inone embodiment, the blob map information is exchanged by sending the map(or just updates) to other data centers at pre-defined intervals. Inanother embodiment, blob map exchange can be performed at the beginningof garbage collection.

FIG. 7 shows the results 700 of a Monte-Carlo simulation of bloboccupancy, according to an embodiment. Specifically, FIG. 7 details theresults of a Monte-Carlo simulation of blob occupancy for a set of 100blobs on two different data centers. The x-axis details the number ofblobs while the y-axis details the percentage of invalidated data in theblobs. As shown in FIG. 7, the mean occupancy is about eighty percent(80%) for both data centers, with about forty percent (40%) of the blobsfully (100%) occupied.

FIG. 8 shows the efficiency resulting from different approaches 800 tochoosing a blob for garbage collection, according to an embodiment. InFIG. 8 it is assumed that a given number of free blobs in data center isneeded (the x-axis). The y-axis details the ratio of blobs freed toblobs copied (which is related to the write amplification) with highervalues indicate lower write amplification. The curve labeled “a freesort” 802 is for a method of selecting the blobs in data center a withthe most free space, without regard to the free space distribution indata center b. The curve runs from freeing 1 blob of space to 10 blobsof space.

The curve labeled “total free sort” 804 is for a method of computing thetotal free space for all the blobs in a group, and selecting those blobswith the most total free space. Referring to FIG. 6, the total freespace for group G01 would be the sum of the free space in 0-01 and 1-01.As can be seen, this method 804 is often more efficient than using onlythe local information.

The curve labeled “mean rank” 806 is a method of sorting the blobs inorder of free space for each data center, then computing a mean rank foreach blob as the average of the ranks of each of the data centers. Theblobs with the best mean rankings are selected for garbage collection.According to FIG. 8, “mean rank” 806 is somewhat better than the “a freesort” 802 method, and appears somewhat worse overall than the “totalfree sort” method 804.

The curve labeled “b free sort” 808 is the result of a method ofselecting the blobs in data center b with the most free space. This isessentially random order for data center a, thus it is not surprisingthat it has the worst behavior. While the simulations 800 are notexpected to be accurate in detail, FIG. 8 highlights the benefits ofusing global information as part of the blob selection mechanism.

If a data center is down (or out of communication), garbage collectionmay still proceed. In such a scenario, the remaining data centersproceed, maintaining the state information as needed. If the parity datacenter is down and/or out of communication with the remaining datacenters, the messages intended for the parity data center must be helduntil the missing data center returns. If the missing data center needsto be reconstructed, garbage collect proceeds as part of this process.For example, if the free space pressure is too high on a given datacenter, a new parity group can be allocated on another data center, andthe garbage collection can continue.

FIG. 9 illustrates a block diagram for a method 900 for reclaiming freespace in a storage system, according to one embodiment. The method 900begins with block 902 with selecting a first blob for reclamation from afirst data center. After selecting the blob for reclamation, the method900 continues with block 904, sending a first message to a second datacenter indicating the first blob is to be reclaimed. The method 900continues with block 906 with sending a second message to the seconddata center after reclaiming the first blob in the first data center.

Upon completion of block 906, the method 900 continues with block 908,receiving a global reclamation complete message from the second datacenter. After receiving the global reclamation complete message, themethod 900 continues with block 910 which indicates the first blob isfree in the map in the first data center. Indication is performed uponreceipt of the global reclamation message from the second data center.After block 910, the method 900 continues with block 912, sending thesecond data center the map indicating free space in the first datacenter.

As will be appreciated by one skilled in the art, aspects of theembodiments may be embodied as a system, method or computer programproduct. Accordingly, aspects of the embodiments may take the form of anentirely hardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,aspects of the embodiments may take the form of a computer programproduct embodied in one or more computer readable medium(s) havingcomputer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of theembodiments may be written in any combination of one or more programminglanguages, including an object oriented programming language such asJava, Smalltalk, C++ or the like and conventional procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The program code may execute entirely on the user's computer,partly on the user's computer, as a stand-alone software package, partlyon the user's computer and partly on a remote computer or entirely onthe remote computer or server. In the latter scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider).

Aspects of the embodiments are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to the embodiments. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, can be implemented by computerprogram instructions. These computer program instructions may beprovided to a processor of a general purpose computer, special purposecomputer, or other programmable data processing apparatus to produce amachine, such that the instructions, which execute via the processor ofthe computer or other programmable data processing apparatus, createmeans for implementing the functions/acts specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of instructions,which comprises one or more executable instructions for implementing thespecified logical function(s). In some alternative implementations, thefunctions noted in the block may occur out of the order noted in thefigures. For example, two blocks shown in succession may, in fact, beexecuted substantially concurrently, or the blocks may sometimes beexecuted in the reverse order, depending upon the functionalityinvolved. It will also be noted that each block of the block diagramsand/or flowchart illustration, and combinations of blocks in the blockdiagrams and/or flowchart illustration, can be implemented by specialpurpose hardware-based systems that perform the specified functions oracts or carry out combinations of special purpose hardware and computerinstructions.

References in the claims to an element in the singular is not intendedto mean “one and only” unless explicitly so stated, but rather “one ormore.” All structural and functional equivalents to the elements of theabove-described exemplary embodiment that are currently known or latercome to be known to those of ordinary skill in the art are intended tobe encompassed by the present claims. No claim element herein is to beconstrued under the provisions of 35 U.S.C. section 112, sixthparagraph, unless the element is expressly recited using the phrase“means for” or “step for.”

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the embodiments.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the embodiments has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the embodiments in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the embodiments. Theembodiments were chosen and described in order to best explain theprinciples of the embodiments and the practical application, and toenable others of ordinary skill in the art to understand the variousembodiments with various modifications as are suited to the particularuse contemplated.

What is claimed is:
 1. A system comprising a computer processor, acomputer-readable hardware storage device, and program code embodiedwith the computer-readable hardware storage device for execution by thecomputer processor to implement a method comprising: receiving aselection of a first blob for reclamation from a first data center;wherein the first blob comprises a plurality of erasure code groups,wherein global parity rotation maintains the plurality of erasure codegroups while minimizing associated write amplification; sending a firstmessage to a second data center indicating the first blob is to bereclaimed; and receiving a global reclamation complete message from thesecond data center; wherein the global reclamation complete messageindicating a second blob in the second data center has been reclaimed,and the first data center and the second data center each maintain localblob occupancy information.
 2. The system of claim 1, furthercomprising: sending a second message to the second data center afterreclaiming the first blob in the first data center; wherein theplurality of erasure code groups is spread across all data centers usingglobal parity rotation.
 3. The system of claim 2, wherein: the globalreclamation complete message being sent in response to the second datacenter receiving a local reclamation complete message from a third datacenter; and the third data center maintains local blob occupancyinformation.
 4. The system of claim 2, wherein reclaiming comprises:reading at least one data set from the first blob; and storing in awrite buffer in the first data center the at least one data set forencoding into an erasure code group in an alternative blob in the firstdata center.
 5. The system of claim 1, wherein upon receipt of theglobal reclamation complete message from the second data center,indicating the first blob is free in a map in the first data center. 6.The system of claim 5, wherein the map is a blob occupancy map, and bloboccupancy maps are exchanged asynchronously between all data centers. 7.The system of claim 5, wherein after indicating the first blob is freein the map in the first data center, sending to the second data centerthe map indicating free space in the first data center.
 8. The system ofclaim 5, wherein selection of the first blob for reclamation from thefirst data center is based on the map indicating free space in the firstdata center.
 9. The system of claim 5, wherein selection of the firstblob for reclamation from the first data center is based on a totalamount of free space of all blobs across all data centers.
 10. Thesystem of claim 5, wherein selection of the first blob for reclamationfrom a first data center is based on a free space rank of all blobsacross all data centers.
 11. An apparatus comprising: a memory storinginstructions; and at least one processor executing the instructions to:receive a selection of a first blob for reclamation from a first datacenter; wherein the first blob comprises a plurality of erasure codegroups, wherein global parity rotation maintains the plurality oferasure code groups while minimizing associated write amplification;send a first message to a second data center indicating the first blobis to be reclaimed; and receive a global reclamation complete messagefrom the second data center; wherein the global reclamation completemessage indicating a second blob in the second data center has beenreclaimed, and the first data center and the second data center eachmaintain local blob occupancy information.
 12. The apparatus of claim11, wherein the at least one processor further executing theinstructions to: send a second message to the second data centers afterreclaiming the first blob in the first data center; wherein theplurality of erasure code groups is spread across all data centers usingglobal parity rotation.
 13. The apparatus of claim 12, wherein: theglobal reclamation complete message being sent in response to the seconddata centers receiving a local reclamation complete message from a thirddata center; and the third data center maintains local blob occupancyinformation.
 14. The apparatus of claim 12, wherein reclaimingcomprises: reading at least one data set from the first blob; andstoring in a write buffer in the first data center the at least one dataset for encoding into an erasure code group in an alternative blob inthe first data center.
 15. The apparatus of claim 11, where upon receiptof the global reclamation message from the second data center,indicating the first blob is free in a map in the first data center. 16.The apparatus of claim 15, wherein the map is a blob occupancy map, andblob occupancy maps are exchanged asynchronously between all datacenters.
 17. The apparatus of claim 15, where after indicating the firstblob is free in the map in the first data center, sending to the seconddata center the map indicating free space in the first data center. 18.The apparatus of claim 15, wherein selection of the first blob forreclamation from the first data center is based on the map indicatingfree space in the first data center.
 19. The apparatus of claim 15,wherein selection of the first blob for reclamation from the first datacenter is based on a total amount of free space of all blobs across alldata centers.
 20. The apparatus of claim 15, wherein selection of thefirst blob for reclamation from a first data center is based on a freespace rank of all blobs across all data centers.